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A Risk-Based Scalable Methodology to Support Strategic Design of An Enterprise Infrastructure

A Risk-Based Scalable Methodology to Support Strategic Design of An Enterprise Infrastructure
支持企业基础设施战略设计的基于风险的可扩展方法
批准号:
0621030
负责人:
Alex Savachkin
金额:
$17.16万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-09-01 至 2010-08-31

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英文摘要
Capacity disruption is one of the most profound influence on risk for globalized enterprises. This grant provides funding for building comprehensive analytical framework for capturing the integrative dynamics of available capacity and demand in enterprise networks exposed to random capacity disruptions. A number of factors defining the network capacity position will be incorporated into the models including, but are not limited to, various modes of capacity degradation and recovery as well as impact of network topology. This mathematical framework will provide a basis for developing a computationally viable methodology to support design of a sustainable and agile enterprise infrastructure. A software prototype with a dynamic database driven analytical engine and a 3D visualization module will be created to facilitate decision making involving network design. The grant will also support the educational component of the research focused on fostering a professional cadre from a spectrum of academic and ethnic backgrounds who can serve as strategic decision makers to effectively mitigate the uncertainties inherent in globalized production and services. An interdisciplinary enterprise risk analysis course will be developed which will uniquely integrate traditional decision making under uncertainty with risk-based design and analysis of capacitated networks.The expected benefits of this research include development of novel mathematical models that will provide foundations to model network risk for topologies of large complexity. If successful, these underlying models and the methodology will enhance resilience and competitiveness of domestic manufacturing enterprises advocating lean manufacturing philosophy. At the same time, the research and educational tasks will contribute to existing and future methodologies that are tailored to model risk inherent in national critical infrastructure systems.
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